Who
Zeus, a US-based manufacturer of high-performance polymer extrusion and custom tubing, serving medical, aerospace, automotive, and industrial sectors.
Case Study
Written by
Abhimanyu Bhandankar
Holds an MBA from Schulich School of Business and a BE in IT. He joined Droplet Lab in July 2019 and now leads sales and marketing.
CEO at Droplet Lab
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Technical Review by
Gurdeep Singh Saini
Holds a BASc in Mechanical Engineering (Ryerson) and an MASc from York University. He focuses on the custom AI behind the instrument.
COO at Droplet Lab
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Executive Summary
Problem
A ~$12K benchtop optical goniometer, read manually, introduced 5–10° of operator-dependent variance in surface energy readings; risking downstream adhesion failures and eroding partner confidence in QC documentation.
Solution
Droplet Lab's $5K smartphone-based goniometer with ML droplet detection, validated against KRÜSS DSA100E and benchmarked in peer-reviewed studies.
Results
±5–10° of operator variance eliminated; readings now reproducible across operators and matched to a KRÜSS DSA100E reference. Five instruments deployed; Gage R&R passed. Factory staff produce lab-grade data — 4 months from first contact, at a fraction of the legacy instrument's cost.
Zeus, at a glance
Industry
Polymer extrusion / custom tubing manufacturing
Applications
Medical, aerospace, automotive, and industrial sectors
QC Stage
In-process inspection
Users
Factory floor inspectors, running 24/7 shifts across multiple plants, with no advanced training in optics or surface science.
Materials / Surfaces Tested
Polymer tubing extrusions
Key Constraints
Minimal workflow disruption; 24/7 operability; high repeatability; multi-facility scalability
A $12K instrument that still couldn't be trusted
How Zeus worked before
Contact angle, the primary method for assessing surface energy on tubing was measured on a ~$12,000 benchtop optical goniometer read manually via the half-angle technique. An inspector aligned a crosshair to the droplet profile and read the angle off an optical protractor by eye. No automated droplet fitting. No digital audit trail. The result depended entirely on the operator at the eyepiece.
Pain points
- Manual alignment introduced consistent human error, no two operators produced identical readings
- Repeatability was insufficient for a high-stakes environment; variance ran to ±5–10°
- At those error levels, adhesion between materials becomes unpredictable, operationally dangerous, not academically inconvenient
- QC documentation shared with partners carried that uncertainty, eroding confidence in process integrity
What Was at Stake
A 5–10° error in contact angle is a material-behaviour question, not a rounding issue. Poor surface energy readings translate directly into adhesion failures, compromised tubing, and QC rejections that ripple into Zeus's medical and aerospace customers' downstream processes. Every report sent to a partner carried the implicit uncertainty of a method that couldn't be independently verified.
What Success Would Require
- Sub-degree accuracy achievable in a production environment, not just a lab
- Operability by factory-floor staff, not only trained technicians
- Compatibility with existing data workflows, including Oracle ERP
- Scalability across multiple facilities without per-site re-engineering
Lab-grade measurement, production-floor workflow
What Was Deployed
Droplet Lab's $5K smartphone-based goniometer system, using the Young–Laplace method for contact angle measurement benchmarked against KRÜSS DSA100E and cited in peer-reviewed publications. A custom tube holder was engineered by Droplet Lab's hardware team to fit Zeus's specific tubing geometry.
What changed, measured side by side
Rollout Timeline
Timeline (high level)
Week 0: Discovery
Zeus contacted Droplet Lab via the website; multiple tubing samples shipped for baseline assessment and comparison against the existing benchtop process.
Week 1-2: Validation
- Virtual demo of system architecture and measurement workflow
- Side-by-side comparison: Droplet Lab system vs. Zeus's manual benchtop on identical samples
- Results and accuracy data returned to the Zeus QA team for review
- Custom tube holder scoped and designed from the sample geometry
Week 3-4: Deployment
Five instruments purchased and delivered to the primary facility; custom tube holder shipped; factory staff onboarded on the test workflow and handling procedures.
Month 2+: Active iteration
24/7 production use generates continuous feedback; ML model retraining, lighting redesign, and ERP integration all initiated from real-world data at this site.
The evidence behind the numbers
Test method
Young Laplace Method
Sample size and operators
100+ samples across 3 operators
Repeatability / reproducibility
Gage R&R study completed and passed
Measured and operational outcomes
Measured Outcomes
Variance eliminated
±5–10° of operator-dependent spread removed readings now reproducible across operators and matched to a KRÜSS DSA100E reference.
Gage R&R
Study completed across 3 operators; instrument passed
Cost & scale
5 instruments at $5K each replaced a ~$12K bench; continuous 24/7 use for 3+ months, no downtime reported.
Operational Outcomes
Factory floor inspectors not lab technicians now consistently produce lab-grade surface energy data as part of standard in-process QC.
Zeus can give partners detailed, traceable, instrument-grade QC documentation instead of operator-estimated readings; a material shift in report credibility.
Continuous production use is generating real-world data that informs ML retraining, hardware refinement, and the ERP integration roadmap.
What Zeus said
"Overall, we've been very impressed. It's been working really well and we really have enjoyed using it. It's a bit different than what we're currently using. It's much more technologically advanced than how we currently do it, which is good. Also, I wanted to let you know we completed our gage R&R study on the unit we have and it performed very well. We’ve been happy with the machine learning add in too, it saves a lot of time on measurements."Brandon Barbee - Corporate Quality Engineer, Development
An active development partnership
Delivered
5 smartphone-based goniometers deployed at primary facility
Custom tube holder designed and delivered
Gage R&R study completed and passed
Continuous 24/7 production use established
In Pilot
ML baseline detection retraining on client's real-world image sets
Lighting redesign with a brighter LED module, mount elevated 2cm to cut reflection
Splitters supplied for simultaneous charging and mouse use
Planned
Desktop interface to remove phone dependency
Oracle ERP API integration to eliminate manual data entry
Client-fabricated collapsible enclosures from open-source designs
Longer-term migration toward RAW cameras